Fraud Detection Dashboard

UX Design Using SAP Fiori Design Principles

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Overview

ACME’s Fraud Detection Dashboard is a SaaS solution designed to empower fraud managers to effectively prioritize high-risk cases, monitor investigator performance, optimize team workflows, and streamline decision-making and productivity through data-driven insights and gamification.

Developed as part of a 4-month academic project for the "stakeholders", Nicole Sharrat, head of product design at Leidos (former VP of Design at FICO), and Daniel Rosenberg (former SVP-Head of Global UX, SAP), who provided domain expertise, problem space information, and guidance. The dashboard addresses the critical challenges of managing fraud in a high-stakes environment.

Goal

The client needs a new SaaS platform to replace outdated analytics software, enabling fraud investigators to respond faster and more accurately to suspected credit card fraud.

Design Challenge: How can we design a dashboard that provides an accurate overview of an investigator's day-to-day case-level load and workflow?

Role

UX designer

Tools

Figma, Axure

Team

Aries Chu

Timeline

Sep - Dec 2024 (16 weeks)

Meet Adam!

Persona

Adam works in the call center for Acme Bank. He works alongside 50 other people during a typical shift. He has been working as a case investigator for 2 years and has been given a mixture of low and high-priority cases to work.

Goals

● Wants to efficiently get through his caseload in the optimal priority order

● He wants to quickly get a clear understanding of what each case is about (which scenario) so that he can shift into the appropriate context, contact the customer, and resolve the issue or override the AI.

Major Pain Points

● He can’t see how many cases are in his queue and how long he has taken to work on each case.

● When he is looking at the cases queue - it’s hard to find the exact information about WHY the transaction has been flagged and then how to find the rest of the information to quickly AND accurately make a decision AND to solve the case.

● Missing tools that allow him to clearly communicate issues or patterns of activity to his peers and managers in a repeatable and consistent way

Challenges:

After reading the design brief, requirements, and dataset, I tried to understand how to translate complex data into a product I was not familiar with. The photo on the right shows a snippet of data I was working with.

Data Set that Needs to be Translated

01 Information Architecture

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Prioritization Matrix


I created a prioritization matrix to assess and rank the frequency of actions performed by Adam, whether frequently or rarely. This matrix helps identify key functionalities and features that should be prominently displayed and easily accessible on the dashboard

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Objext Attribute Matrix

I created an object-attribute matrix that lists objects and their related attributes, ensuring alignment with the object-action matrix. This helps me organize detailed information for each object and determine what should be included in the dashboard.

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Object action matrix

Before designing the screens, I created an object-action matrix to outline the relationships between all necessary objects and actions in the system. This matrix facilitates high-level thinking about which elements should be included in the dashboard and how Adam will interact with them.

Sketching

With a clear understanding of the key information to be displayed, I began sketching the overview page. My focus was on designing a layout that effectively presents a high-level performance overview while ensuring an intuitive and efficient case-solving experience on the dashboard.

First Design

02 First Design

This was my initial design for fraud detection. While it was functional for investigators, it was only effective from an external perspective. However, it lacked elements that motivated investigators, making their work feel tedious and less engaging.

03 Designing Gamification for Investigators

The gamification system was designed to motivate investigators through rewards, recognition, and contribution opportunities. Investigators' success depended on engaging well-crafted games. Key elements included:

Game Economy: Points and rewards based on investigator performance, with customizable thresholds set by managers.

Engagement Loop: Investigators earned points, badges, and leaderboard rankings, while managers adjusted challenges based on outcomes.

Metrics-Driven Design: Managers were evaluated on investigator productivity and game success, encouraging strategic challenge creation. This approach enhanced investigator engagement and aligned with organizational goals, positioning managers as facilitators of team success.

This approach enhanced investigator engagement and aligned with organizational goals and team success.

Implementing a Scoring System

To enhance investigator motivation and improve case performance, I introduced a structured point system integrated with missions. This approach provided clear objectives, measurable progress, and tangible rewards, fostering a sense of achievement and engagement among investigators.

By earning points for completing missions, investigators were encouraged to stay proactive and focused, ultimately driving better outcomes in fraud detection..

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Leaderboard

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Prizes for Cases

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Prize for the First Few Places

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Missions to Earn More Points

Final Design

04 Final Design

The screen was revised based on recommendations from Professor Daniel Rosenberg (former SVP and Head of Global UX at SAP), along with several other refinements. Professor Rosenberg praised the design, stating that "there is nothing much to critique." This design enhances investigator engagement by making the interface intuitive while also providing incentives and motivation to continue their work.

Learnings

Working on this dashboard taught me how to balance two opposing forces: long-term insight and real-time action. Investigators need clarity quickly, but they also need the flexibility to dive deeper when necessary. That balance shaped every design decision.

This project changed how I think about systems—not just how they work, but how they feel.

After testing the final prototype and gathering feedback, the design effectively met users’ needs. This new platform enables fraud investigators to work more efficiently, detect fraud faster, and with greater accuracy than the previous software.

Key Takeaways:

  • The value of proactive communication: Engaging with the PM early to clarify user needs was essential to aligning the design with real-world use cases.

  • Continuous feedback integration: Seeking and incorporating feedback throughout the design process ensured that the final product met user expectations and addressed pain points.

This experience reinforced my belief that great UX is about more than just aesthetics—it’s about designing for decisions that drive real impact.